Age of Air as a diagnostic for transport time-scales in global models

Abstract

Abstract. This paper presents the first results of an age of air (AoA) inter-comparison of six global transport models. Following a protocol, three global circulation models and three chemistry transport models simulated five tracers with boundary conditions that grow linearly in time. This allows for an evaluation of the AoA and transport times associated with inter-hemispheric transport, vertical mixing in the troposphere, transport to and in the stratosphere, and transport of air masses between land and ocean. Since AoA is not a directly measurable quantity in the atmosphere, simulations of 222 Rn and SF 6 were also requested. 5We focus this first analysis on averages over the period 2000-2010, taken from longer simulations covering the 1988 -2014 period. We find that two models, NIES and TOMCAT, show substantially slower vertical mixing in the troposphere compared to other models (LMDZ, TM5, EMAC, and ACTM). However, while the TOMCAT model, as used here, has slow transport between the hemispheres and between land and ocean, the NIES model shows efficient horizontal mixing and a smaller latitudinal gradient in SF 6 compared to the other models and observations. We find consistent differences between models concerning 10 vertical mixing of the troposphere, expressed as AoA differences and modeled 222Rn gradients between 950 and 500 hPa.All models agree, however, on an interesting asymmetry in inter-hemispheric mixing, with faster transport from the Northern hemisphere surface to the Southern hemisphere than vice versa. This is attributed to a rectifier caused by a stronger seasonal cycle in boundary layer venting over Northern hemispheric landmasses, and possibly to a related asymmetric position of the inter-tropical convergence zone. The calculated AoA in the upper stratosphere varies considerably among the models (4 -7 15 years). Finally, we find that the inter-model differences are generally larger than differences in AoA that result from using the same model with a different resolution or convective parameterisation. Taken together, the AoA model inter-comparison provides a useful addition to traditional approaches to evaluate transport time scales. Results highlight that inter-model differences 1 Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-262 Manuscript under review for journal Geosci. Model Dev. Discussion started: 7 November 2017 c Author(s) 2017. CC BY 4.0 License. associated with resolved transport (advection) and parameterised transport (convection, boundary layer mixing) are still large, and require further analysis. For this purpose, all model output and analysis software is available.

Age of martian air: Time scales for martian atmospheric transport

“…However, as discussed in Waugh et al (2016) with respect to polar vortices, it is more appropriate to compare transport in the Martian atmosphere with that in Earth's troposphere. The mean time since tropospheric air has been at the surface is much less than in the stratosphere, with mean ages generally less than 100 days for a global surface source region (Krol et al, 2017) and generally comparable with the mean ages presented here.…”

“…Specifically, we use the MarsWRF general circulation model to calculate the mean time since air in the Martian atmosphere was in the low-to mid-latitude boundary layer. Similar calculations of the "mean age" (or age of air) are common in studies of transport in Earth's stratosphere (e.g., Hall and Plumb, 1994;Waugh and Hall, 2002) and, more recently, in Earth's troposphere Orbe et al, 2017;Krol et al 2017). The mean transit time to a location is a fundamental aspect of the transport, and has been used in studies of Earth's atmosphere to quantify the propagation of changes in concentration of constituents (e.g.…”

Quantifying the Impact of Atmospheric Transport Uncertainty on CO2 Surface Flux Estimates

“…After almost a decade of investigation into the cause of this bias, it was discovered that the convective transport parameterization in TM5 based on Tiedtke () was not representing the vertical mass fluxes of the parent ECMWF model. By this time, however, the ERA‐i reanalysis had begun archiving these convective mass fluxes and became possible to apply them directly in TM5 instead of rediagnosing convective transport within the daughter model (Krol et al, ; Tsuruta et al, ). This “convection fix” (red symbols in Figure ) almost completely removed the excessive interhemispheric gradient of surface SF 6 manifested by the earlier TM5 configuration.…”

“…It has only a minor sink in the mesosphere, resulting in an extremely long atmospheric lifetime estimated somewhere between 850 and 3,200˜years (Maiss & Brenninkmeijer, 1998;Ray et al, 2017). Due to its near-conservation in the atmosphere and to its surface emissions being related to electrical power consumption, it is analogous to fossil fuel-derived CO 2 and is frequently used to evaluate the large-scale transport in atmospheric models (Denning et al, 1999;Krol et al, 2017;Patra et al, 2011;Peters et al, 2004). The global atmospheric growth rate of SF 6 , and hence its global emissions source, is particularly well constrained by available observations (Levin et al, 2010).…”

Reply to Reviewer 1

“…Code availability. The AoA protocol and analysis software in the form of a Jupyter Notebook (Python) are available to the community through github (https://github.com/maartenkrol/AoA) and are available at https://doi.org/10.23728/b2share.d6849238d65f435 c8f022221f2107cdd (Krol et al, 2018). The Python notebook aoa_paper.ipynb needs AoA_tools.py.…”